Brazil has one of the emerging world's most advanced consumer credit bureau systems. Serasa Experian and SPC Brasil reach most formally employed adults who hold bank accounts. Yet that reach hides a major gap: about 35 million adults are thin-file or no-file. Even that estimate misses many people with files so limited that conventional scoring models produce no clear result.
To see alternative data's role in Brazil, lenders must examine both the source of the gap and the form these alternative signals take in this market.
How Brazil's Bureau System Produces Exclusion
Brazil's credit infrastructure exceeds that of most emerging markets. The positive data sharing framework introduced in 2019 substantially broadened bureau coverage. Cadastro Positivo moved from opt-in to opt-out under regulation and brought millions of records into Serasa's database. These changes delivered real gains.
The obstacle is structural rather than technical. Bureau scores capture formal financial conduct: bank account activity, credit card usage, installment repayment, and payroll deduction records. About 65 million Brazilians are unbanked or underbanked, so they produce little such data, not due to poor money management, but because they use informal channels. They pay utility bills at lottery terminals (casas lotericas), recharge prepaid mobile plans instead of maintaining contracts, and receive Pix payments from relatives or employers rather than payroll deposits. Bureau records do not reliably capture these behaviors.
Thus, a financially active population remains unseen by conventional scoring. Closing that visibility gap is the role of alternative data.
Alternative Data in Brazil's Specific Context
Brazil offers particular structural benefits for gathering alternative data. Mobile use is extremely widespread compared with formal banking access. Pix, Banco Central do Brasil's instant payment system launched in 2020, handles billions of monthly transactions and has gained substantial adoption across income groups. Utility payment records are broad because electricity reaches nearly all areas, including low-income communities.
For alternative scoring, this creates a deeper signal pool than many comparable markets offer. A borrower in a favela or rural municipality may lack a bank account yet show 24 months of steady mobile recharges, regular utility payments available through permissioned channels, and Pix activity indicating stable income and disciplined cash flow management.
Supersymm built its signal layer around these Brazil-specific patterns. Consistency in mobile recharge amounts and frequency is one of our stronger predictors. Regular utility payments, especially electricity, have shown predictive value across geographic and income settings in our early-access pilots. Geolocation stability, or consistent home and work locations over a 90 day period, is associated with the life stability that predicts repayment.
Lender View: Addressable Market, Not Social Mission
Alternative data is sometimes presented solely as a financial inclusion instrument. That view is valid but incomplete. Lenders need to know whether thin-file borrowers are creditworthy and simply missed by current infrastructure. Evidence indicates that they are.
Take a borrower who first enters the bureau through a loan scored by Supersymm. Successful repayment creates a bureau record and starts the borrower toward conventional credit. The originating lender gains more than one transaction: it begins a relationship with a customer likely to expand financial product use over time. This is the acquisition case for thin-file lending, entering the relationship before competition reaches the segment.
Brazil's digital lending market has expanded quickly, making competition for bureau-file borrowers already intense. Much of the real growth opportunity lies where most lenders have not yet focused. Alternative data makes those segments actionable.
LGPD and Data Governance
Brazil's Lei Geral de Protecao de Dados (LGPD) creates a data protection framework and significant duties for systems using personal data in credit decisions. We make no certification claim here. Still, lenders and their vendors must operate within these requirements when incorporating alternative data sources.
Under LGPD, alternative credit scoring chiefly raises consent, purpose limitation, and data subject rights. Borrowers should know that behavioral signals can inform credit assessment, with specific disclosure rather than generic terms and conditions. Purpose limitation also means data gathered for one purpose cannot be used for credit scoring without separate consent.
Supersymm handles only signals the borrower has expressly allowed the lender to share. We keep derived features, not raw behavioral data, and delete those features 12 months after the last lender query. This prevents us from creating a behavioral data repository that could produce continuing regulatory exposure for lender partners. Lenders retain responsibility for consent and documentation. Our system supports those compliance duties instead of adding complexity.
Alternative Data in Practice
In Brazil, alternative data does not replace bureau data. Bureau coverage is genuine, and its data is dependable for the people covered. In practice, integration occurs when a bureau inquiry returns thin-file or no-hit applicants. Most lenders decline these applicants because they lack an evaluation signal, not because the applicants are necessarily unqualified.
For Brazilian lenders, alternative credit scoring addresses a precise issue: it fills the point where conventional data ends rather than rebuilding the credit decision process. Brazil's 35 million thin-file adults are not one uniform risk category. They include many creditworthy borrowers whom the existing system cannot recognize. Alternative data enables that recognition.